import pandas as pd
import numpy as np
import plotly.graph_objects as go
import plotly.express as px

covid19_confirmed_cases_link = "time_series_covid19_confirmed_global.csv"
covid19_death_cases_link = "time_series_covid19_deaths_global.csv"
covid19_recovered_cases_link = "time_series_covid19_recovered_global.csv"
covid19_countries_cases_link =  "cases_country.csv"

confirmed_df = pd.read_csv(covid19_confirmed_cases_link)
death_df = pd.read_csv(covid19_death_cases_link)
recovered_df = pd.read_csv(covid19_recovered_cases_link)
cases_countries_df  = pd.read_csv(covid19_countries_cases_link)
print(confirmed_df.shape)
print(death_df.shape)
print(recovered_df.shape)
print(cases_countries_df.shape)

confirmed_df[confirmed_df["Country/Region"] == "Australia"]

confirmed_df["Country/Region"].nunique()

confirmed_df = confirmed_df.replace(np.nan, '', regex = True)
death_df = death_df.replace(np.nan, '', regex = True)
recovered_df = recovered_df.replace(np.nan, '', regex = True)
cases_countries_df = cases_countries_df.replace(np.nan, '', regex = True)

confirmed_df

confirmed_df.columns

cases_countries_df

global_data = cases_countries_df.copy().drop(['Country_Region', 'Last_Update', 'Lat', 'Long_', 'Incident_Rate', 'People_Tested', 'People_Hospitalized', 'Mortality_Rate', 'UID' , 'ISO3'], axis=1)
global_summary = pd.DataFrame(global_data.sum()).transpose()
global_summary.style.format("{:0.0f}")

confirmed_ts = confirmed_df.copy().drop(['Lat', 'Long','Province/State', 'Country/Region'], axis=1)
confirmed_ts_summary = confirmed_ts.sum()

confirmed_ts_summary

fig_1 = go.Figure(data=go.Scatter(x=confirmed_ts_summary.index, y=confirmed_ts_summary.values,mode = 'lines+markers'))
fig_1.update_layout(title='Total confirmed coronavirus cases globally', yaxis_title = 'confirmed_cases', xaxis_tickangle = 300)

fig_1.show()

#here we are initializing a color array
color_arr = px.colors.qualitative.Dark24

def draw_plot(ts_array, ts_label, title, colors, mode_size,line_size, x_axis_title, y_axis_title, tickangle = 0, y_axis_type=''):
    #initilalizing figure
    fig = go.Figure()
    #adding all traces
    for index, ts in enumerate(ts_array):
        fig.add_trace(go.Scatter(x=ts.index,
                                 y=ts.values,
                                 name = ts_label[index],
                                 line=dict(color=colors[index], width=line_size[index]),connectgaps = True),)
    
    #base x_axis properties
    x_axis_dict = dict(showline=True,
                       showgrid=True,
                       showticklabels=True,
                       linecolor='rgb(200,200,200)',
                       linewidth=2,
                       ticks='outside',
                       tickfont=dict(family='Arial', size=12, color='rgb(90,90,90)',))
    
    # x_axis parameters
    if x_axis_title:
        x_axis_dict['title'] = x_axis_title
    
    if tickangle > 0:
        x_axis_dict['tickangle'] =tickangle
        
        
    #y_axis properties
    y_axis_dict = dict(showline=True,
                   showgrid=True,
                   showticklabels=True,
                   linecolor='rgb(200,200,200)',
                   linewidth=2,)
    
    #y_axis parameters
    if y_axis_type != "":
        y_axis_dict['type'] = y_axis_type
    
    if y_axis_title:
        y_axis_dict['title'] = y_axis_title
        
        
    #updating the layout
    fig.update_layout(xaxis = x_axis_dict,
                      yaxis = y_axis_dict,
                      autosize=True,
                      margin=dict(autoexpand=True,l=100,r=20, t=110,),
                      showlegend =True,
                     )
    
    #annotations for any basic graph
    annotations = []
    #title
    annotations.append(dict(xref='paper', yref='paper', x=0.0, y= 1.05, xanchor='left', yanchor='bottom',text=title,
                            font=dict(family='Arial' ,size= 16, color='rgb(40,40,40)'),showarrow=False))
    
    
#     #adding annotationsi params
#     if len(additional_annotations) > 0:
#         annotations.append(additional_annotations)
        
#     #updating the layout
#     fig.update_layout(annotations=annotations)
    
    return fig
    
    
    

confirmed_agg_ts  = confirmed_df.copy().drop(['Lat', 'Long','Province/State', 'Country/Region'],axis=1).sum()
death_agg_ts  = death_df.copy().drop(['Lat', 'Long','Province/State', 'Country/Region'],axis=1).sum()
recovered_agg_ts  = recovered_df.copy().drop(['Lat', 'Long','Province/State', 'Country/Region'],axis=1).sum()

#now  as thier is no timeseries data for the active cases  therefore we calculated it simply by list comprehension
active_agg_ts =pd.Series(
                data=np.array(
                [x1-x2-x3 for (x1,x2,x3) in zip(confirmed_agg_ts.values,death_agg_ts.values,recovered_agg_ts.values)]),
                index=confirmed_agg_ts.index)

ts_array = [confirmed_agg_ts, active_agg_ts, recovered_agg_ts, death_agg_ts]
labels = ['Confirmed', 'Active', 'Recovered', 'Deaths']
colors = [color_arr[5], color_arr[0], color_arr[2], color_arr[3]]
mode_size = [8,8,12,8]
line_size = [2,2,4,2]

#now we call the draw_plot function that we defined above
fig_2 = draw_plot(ts_array = ts_array,
                  ts_label = labels,
                  title = "Covid 19 cases status  from 22nd jan to 9 august 2020",
                  colors = colors, mode_size = mode_size,
                  line_size = line_size,
                  x_axis_title = "Date",
                  y_axis_title = "case-count",
                  tickangle = 300,
                  y_axis_type = '')

fig_2.show()

cases_countries_df

cases_countries_df.copy().drop(
    ['Lat', 'Long_','Last_Update'],axis = 1).sort_values('Confirmed', ascending = False).reset_index(drop=True).style.bar(
align = "left", width=198, color= '#ff781c')